R/qqunifSimPower.R

In MKpower: Power Analysis and Sample Size Calculation

qqunif <- function(x, ...){
  UseMethod("qqunif")
}
qqunif.default <- function(x, min = 0, max = 1, ...){
  DF <- data.frame(sample = x)
  dps <- list(min = min, max = max)
  gg <- ggplot(DF, aes_string(sample = "sample")) + 
    stat_qq_point(distribution = "unif", dparams = dps) +
    stat_qq_band(distribution = "unif", dparams = dps) +
    qqplotr::stat_qq_line(distribution = "unif", dparams = dps) +
    labs(x = "Theoretical Quantiles", y = "Sample Quantiles") 
  gg
}
qqunif.sim.power.ttest <- function(x, color.line = "orange", shape = 19, size = 1, 
                                   alpha = 1, ...){
  iter <- x$SetUp$iter
  sig.level <- x$SetUp$sig.level
  DF <- data.frame(pvalue = c(x$Classical$H1$pvalue,
                              x$Welch$H1$pvalue,
                              x$Hsu$H1$pvalue),
                   test = c(rep("Classical two-sample t-test", iter),
                            rep("Welch two-sample t-test", iter),
                            rep("Hsu two-sample t-test", iter)),
                   hypothesis = rep("H1", 3*iter))
  if(!is.null(x$Classical$H0)){
    DF1 <- data.frame(pvalue = c(x$Classical$H0$pvalue,
                                 x$Welch$H0$pvalue,
                                 x$Hsu$H0$pvalue),
                      test = c(rep("Classical two-sample t-test", iter),
                               rep("Welch two-sample t-test", iter),
                               rep("Hsu two-sample t-test", iter)),
                      hypothesis = rep("H0", 3*iter))
    DF <- rbind(DF, DF1)
  }
  DF$test <- factor(DF$test, levels = c("Classical two-sample t-test",
                                        "Welch two-sample t-test",
                                        "Hsu two-sample t-test"))
  if(!is.null(x$Classical$H0)){
    Lab <- round(c(sum(x$Classical$H1$pvalue < sig.level)/iter,
                   sum(x$Welch$H1$pvalue < sig.level)/iter,
                   sum(x$Hsu$H1$pvalue < sig.level)/iter,
                   sum(x$Classical$H0$pvalue < sig.level)/iter,
                   sum(x$Welch$H0$pvalue < sig.level)/iter,
                   sum(x$Hsu$H0$pvalue < sig.level)/iter), 4)
    Lab[1:3] <- paste("emp. power:", Lab[1:3])
    Lab[4:6] <- paste("emp. type-I-error:", Lab[4:6])
    DF.text <- data.frame(test = rep(c("Classical two-sample t-test",
                                       "Welch two-sample t-test",
                                       "Hsu two-sample t-test"), 2),
                          hypothesis = c(rep("H1", 3), rep("H0", 3)),
                          label = Lab)
    gg <- ggplot(DF, aes_string(sample = "pvalue")) + 
      stat_qq_point(distribution = "unif", shape = shape, size = size, alpha = alpha) +
      #      stat_qq_band(distribution = "unif", color = "red") +
      qqplotr::stat_qq_line(distribution = "unif", color = color.line) +
      geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"), 
                vjust = 2, inherit.aes = FALSE) +
      labs(x = "Theoretical Quantiles", y = "Sample Quantiles") +
      facet_grid(hypothesis ~ test, scales = "free_y")
  }else{
    Lab <- round(c(sum(x$Classical$H1$pvalue < sig.level)/iter,
                   sum(x$Welch$H1$pvalue < sig.level)/iter,
                   sum(x$Hsu$H1$pvalue < sig.level)/iter), 4)
    Lab <- paste("emp. power:", Lab)
    DF.text <- data.frame(test = c("Classical two-sample t-test",
                                   "Welch two-sample t-test",
                                   "Hsu two-sample t-test"),
                          hypothesis = rep("H1", 3),
                          label = Lab)
    gg <- ggplot(DF, aes_string(sample = "pvalue")) + 
      stat_qq_point(distribution = "unif", shape = shape, size = size, alpha = alpha) +
      #      stat_qq_band(distribution = "unif", color = "red") +
      qqplotr::stat_qq_line(distribution = "unif", color = color.line) +
      geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"), 
                vjust = 2, inherit.aes = FALSE) +
      labs(x = "Theoretical Quantiles", y = "Sample Quantiles") +
      facet_grid(~ test)
  }
  gg
}
qqunif.sim.power.wtest <- function(x, color.line = "orange", shape = 19, size = 1, 
                                   alpha = 1, ...){
  iter <- x$SetUp$iter
  sig.level <- x$SetUp$sig.level
  approximate <- x$SetUp$approximate
  if(approximate){
    DF <- data.frame(pvalue = c(x$Exact$H1$pvalue,
                                x$Asymptotic$H1$pvalue,
                                x$Approximate$H1$pvalue),
                     test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
                              rep("Asymptotic Wilcoxon-Mann-Whitney test", iter),
                              rep("Approximate Wilcoxon-Mann-Whitney test", iter)),
                     hypothesis = rep("H1", 3*iter))
  }else{
    DF <- data.frame(pvalue = c(x$Exact$H1$pvalue,
                                x$Asymptotic$H1$pvalue),
                     test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
                              rep("Asymptotic Wilcoxon-Mann-Whitney test", iter)),
                     hypothesis = rep("H1", 2*iter))
  }
  if(!is.null(x$Exact$H0)){
    if(approximate){
      DF1 <- data.frame(pvalue = c(x$Exact$H0$pvalue,
                                  x$Asymptotic$H0$pvalue,
                                  x$Approximate$H0$pvalue),
                       test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
                                rep("Asymptotic Wilcoxon-Mann-Whitney test", iter),
                                rep("Approximate Wilcoxon-Mann-Whitney test", iter)),
                       hypothesis = rep("H0", 3*iter))
    }else{
      DF1 <- data.frame(pvalue = c(x$Exact$H0$pvalue,
                                   x$Asymptotic$H0$pvalue),
                       test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
                                rep("Asymptotic Wilcoxon-Mann-Whitney test", iter)),
                       hypothesis = rep("H0", 2*iter))
    }
    DF <- rbind(DF, DF1)
  }
  if(approximate){
    DF$test <- factor(DF$test, levels = c("Exact Wilcoxon-Mann-Whitney test",
                                          "Asymptotic Wilcoxon-Mann-Whitney test",
                                          "Approximate Wilcoxon-Mann-Whitney test"))
  }else{
    DF$test <- factor(DF$test, levels = c("Exact Wilcoxon-Mann-Whitney test",
                                          "Asymptotic Wilcoxon-Mann-Whitney test"))
  }
  if(!is.null(x$Exact$H0)){
    if(approximate){
      Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
                     sum(x$Approximate$H1$pvalue < sig.level)/iter,
                     sum(x$Exact$H0$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H0$pvalue < sig.level)/iter,
                     sum(x$Approximate$H0$pvalue < sig.level)/iter), 4)
      Lab[1:3] <- paste("emp. power:", Lab[1:3])
      Lab[4:6] <- paste("emp. type-I-error:", Lab[4:6])
      DF.text <- data.frame(test = rep(c("Exact Wilcoxon-Mann-Whitney test",
                                         "Asymptotic Wilcoxon-Mann-Whitney test",
                                         "Approximate Wilcoxon-Mann-Whitney test"), 2),
                            hypothesis = c(rep("H1", 3), rep("H0", 3)),
                            label = Lab)
    }else{
      Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
                     sum(x$Exact$H0$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H0$pvalue < sig.level)/iter), 4)
      Lab[1:2] <- paste("emp. power:", Lab[1:2])
      Lab[3:4] <- paste("emp. type-I-error:", Lab[3:4])
      DF.text <- data.frame(test = rep(c("Exact Wilcoxon-Mann-Whitney test",
                                         "Asymptotic Wilcoxon-Mann-Whitney test"), 2),
                            hypothesis = c(rep("H1", 2), rep("H0", 2)),
                            label = Lab)
    }
    gg <- ggplot(DF, aes_string(sample = "pvalue")) + 
      stat_qq_point(distribution = "unif", shape = shape, size = size, alpha = alpha) +
      #      stat_qq_band(distribution = "unif", color = "red") +
      qqplotr::stat_qq_line(distribution = "unif", color = color.line) +
      geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"), 
                vjust = 2, inherit.aes = FALSE) +
      labs(x = "Theoretical Quantiles", y = "Sample Quantiles") +
      facet_grid(hypothesis ~ test, scales = "free_y")
  }else{
    if(approximate){
      Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
                     sum(x$Approxmiate$H1$pvalue < sig.level)/iter), 4)
      Lab <- paste("emp. power:", Lab)
      DF.text <- data.frame(test = c("Exact Wilcoxon-Mann-Whitney test",
                                     "Asymptotic Wilcoxon-Mann-Whitney test",
                                     "Approximate Wilcoxon-Mann-Whitney test"),
                            hypothesis = rep("H1", 3),
                            label = Lab)
    }else{
      Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
                     sum(x$Asymptotic$H1$pvalue < sig.level)/iter), 4)
      Lab <- paste("emp. power:", Lab)
      DF.text <- data.frame(test = c("Exact Wilcoxon-Mann-Whitney test",
                                     "Asymptotic Wilcoxon-Mann-Whitney test"),
                            hypothesis = rep("H1", 2),
                            label = Lab)
    }
    gg <- ggplot(DF, aes_string(sample = "pvalue")) + 
      stat_qq_point(distribution = "unif", shape = shape, size = size, alpha = alpha) +
      #      stat_qq_band(distribution = "unif", color = "red") +
      qqplotr::stat_qq_line(distribution = "unif", color = color.line) +
      geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"), 
                vjust = 2, inherit.aes = FALSE) +
      labs(x = "Theoretical Quantiles", y = "Sample Quantiles") +
      facet_grid(~ test)
  }
  gg
}